Literature DB >> 34597125

Immune checkpoint blockade sensitivity and progression-free survival associates with baseline CD8+ T cell clone size and cytotoxicity.

Robert A Watson1,2,3, Orion Tong1,2, Rosalin Cooper1,2, Chelsea A Taylor1,2, Piyush K Sharma1,2, Alba Verge de Los Aires1,2, Elise A Mahé1,2, Hélène Ruffieux3, Isar Nassiri1,2, Mark R Middleton2,4, Benjamin P Fairfax1,2,4.   

Abstract

The antitumor action of immune checkpoint blockade (ICB) is primarily mediated by CD8+ T cells. How sensitivity to ICB varies across CD8+ T cell subsets and clonotypes and the relationship of these with clinical outcome is unclear. To explore this, we used single-cell V(D)J and RNA-sequencing to track gene expression changes elicited by ICB across individual peripheral CD8+ T cell clones, identify baseline markers of CD8+ T cell clonal sensitivity, and chart how CD8+ T cell transcriptional changes vary according to phenotypic subset and clonal size. We identified seven subsets of CD8+ T cells with divergent reactivity to ICB and found that the cytotoxic effector subset showed the greatest number of differentially expressed genes while remaining stable in clonal size after ICB. At the level of CD8+ T cell clonotypes, we found a relationship between transcriptional changes and clone size, with large clones showing a greater number of differentially regulated genes enriched for pathways including T cell receptor (TCR) signaling. Cytotoxic CD8+ effector clones were more likely to persist following ICB and were more likely to correspond with public tumor-infiltrating lymphocyte clonotypes. Last, we demonstrated that individuals whose CD8+ T cell pretreatment showed low cytotoxicity and had fewer expanded clones typically had worse outcomes after ICB treatment. This work further advances understanding of the molecular determinants of ICB response, assisting in the search for peripheral prognostic biomarkers and highlighting the importance of the baseline CD8+ immune landscape in determining ICB response in metastatic melanoma.

Entities:  

Mesh:

Substances:

Year:  2021        PMID: 34597125      PMCID: PMC7612602          DOI: 10.1126/sciimmunol.abj8825

Source DB:  PubMed          Journal:  Sci Immunol        ISSN: 2470-9468


  49 in total

1.  MiXCR: software for comprehensive adaptive immunity profiling.

Authors:  Dmitriy A Bolotin; Stanislav Poslavsky; Igor Mitrophanov; Mikhail Shugay; Ilgar Z Mamedov; Ekaterina V Putintseva; Dmitriy M Chudakov
Journal:  Nat Methods       Date:  2015-05       Impact factor: 28.547

2.  Proliferation of PD-1+ CD8 T cells in peripheral blood after PD-1-targeted therapy in lung cancer patients.

Authors:  Alice O Kamphorst; Rathi N Pillai; Shu Yang; Tahseen H Nasti; Rama S Akondy; Andreas Wieland; Gabriel L Sica; Ke Yu; Lydia Koenig; Nikita T Patel; Madhusmita Behera; Hong Wu; Megan McCausland; Zhengjia Chen; Chao Zhang; Fadlo R Khuri; Taofeek K Owonikoko; Rafi Ahmed; Suresh S Ramalingam
Journal:  Proc Natl Acad Sci U S A       Date:  2017-04-26       Impact factor: 11.205

3.  Complex heatmaps reveal patterns and correlations in multidimensional genomic data.

Authors:  Zuguang Gu; Roland Eils; Matthias Schlesner
Journal:  Bioinformatics       Date:  2016-05-20       Impact factor: 6.937

4.  Integrating single-cell transcriptomic data across different conditions, technologies, and species.

Authors:  Andrew Butler; Paul Hoffman; Peter Smibert; Efthymia Papalexi; Rahul Satija
Journal:  Nat Biotechnol       Date:  2018-04-02       Impact factor: 54.908

5.  Clustering trees: a visualization for evaluating clusterings at multiple resolutions.

Authors:  Luke Zappia; Alicia Oshlack
Journal:  Gigascience       Date:  2018-07-01       Impact factor: 6.524

6.  A genetics-led approach defines the drug target landscape of 30 immune-related traits.

Authors:  Hai Fang; Hans De Wolf; Bogdan Knezevic; Katie L Burnham; Julie Osgood; Anna Sanniti; Alicia Lledó Lara; Silva Kasela; Stephane De Cesco; Jörg K Wegner; Lahiru Handunnetthi; Fiona E McCann; Liye Chen; Takuya Sekine; Paul E Brennan; Brian D Marsden; David Damerell; Chris A O'Callaghan; Chas Bountra; Paul Bowness; Yvonne Sundström; Lili Milani; Louise Berg; Hinrich W Göhlmann; Pieter J Peeters; Benjamin P Fairfax; Michael Sundström; Julian C Knight
Journal:  Nat Genet       Date:  2019-06-28       Impact factor: 38.330

7.  Peripheral T cell expansion predicts tumour infiltration and clinical response.

Authors:  Thomas D Wu; Shravan Madireddi; Patricia E de Almeida; Romain Banchereau; Ying-Jiun J Chen; Avantika S Chitre; Eugene Y Chiang; Hina Iftikhar; William E O'Gorman; Amelia Au-Yeung; Chikara Takahashi; Leonard D Goldstein; Chungkee Poon; Shilpa Keerthivasan; Denise E de Almeida Nagata; Xiangnan Du; Hyang-Mi Lee; Karl L Banta; Sanjeev Mariathasan; Meghna Das Thakur; Mahrukh A Huseni; Marcus Ballinger; Ivette Estay; Patrick Caplazi; Zora Modrusan; Lélia Delamarre; Ira Mellman; Richard Bourgon; Jane L Grogan
Journal:  Nature       Date:  2020-02-26       Impact factor: 69.504

8.  DGCA: A comprehensive R package for Differential Gene Correlation Analysis.

Authors:  Andrew T McKenzie; Igor Katsyv; Won-Min Song; Minghui Wang; Bin Zhang
Journal:  BMC Syst Biol       Date:  2016-11-15

9.  UpSetR: an R package for the visualization of intersecting sets and their properties.

Authors:  Jake R Conway; Alexander Lex; Nils Gehlenborg
Journal:  Bioinformatics       Date:  2017-09-15       Impact factor: 6.937

10.  Peripheral CD8+ T cell characteristics associated with durable responses to immune checkpoint blockade in patients with metastatic melanoma.

Authors:  Benjamin P Fairfax; Chelsea A Taylor; Robert A Watson; Isar Nassiri; Sara Danielli; Hai Fang; Elise A Mahé; Rosalin Cooper; Victoria Woodcock; Zoe Traill; M Hussein Al-Mossawi; Julian C Knight; Paul Klenerman; Miranda Payne; Mark R Middleton
Journal:  Nat Med       Date:  2020-02-10       Impact factor: 53.440

View more
  7 in total

Review 1.  TCR-sequencing in cancer and autoimmunity: barcodes and beyond.

Authors:  Kristen E Pauken; Kaitlyn A Lagattuta; Benjamin Y Lu; Liliana E Lucca; Adil I Daud; David A Hafler; Harriet M Kluger; Soumya Raychaudhuri; Arlene H Sharpe
Journal:  Trends Immunol       Date:  2022-01-25       Impact factor: 16.687

2.  Peripheral T cell cytotoxicity predicts the efficacy of anti-PD-1 therapy for advanced non-small cell lung cancer patients.

Authors:  Kota Iwahori; Takeshi Uenami; Yukihiro Yano; Toshihiko Ueda; Mari Tone; Yujiro Naito; Yasuhiko Suga; Kiyoharu Fukushima; Takayuki Shiroyama; Kotaro Miyake; Shohei Koyama; Haruhiko Hirata; Izumi Nagatomo; Hiroshi Kida; Masahide Mori; Yoshito Takeda; Atsushi Kumanogoh; Hisashi Wada
Journal:  Sci Rep       Date:  2022-10-19       Impact factor: 4.996

Review 3.  Steroid-Refractory Gut Graft-Versus-Host Disease: What We Have Learned From Basic Immunology and Experimental Mouse Model.

Authors:  Qingxiao Song; Ubaydah Nasri; Defu Zeng
Journal:  Front Immunol       Date:  2022-02-18       Impact factor: 7.561

4.  Dynamic changes in peripheral blood monocytes early after anti-PD-1 therapy predict clinical outcomes in hepatocellular carcinoma.

Authors:  Seung Hyuck Jeon; Yong Joon Lee; Hyung-Don Kim; Heejin Nam; Baek-Yeol Ryoo; Su-Hyung Park; Changhoon Yoo; Eui-Cheol Shin
Journal:  Cancer Immunol Immunother       Date:  2022-07-28       Impact factor: 6.630

5.  Single-cell RNA-sequencing reveals predictive features of response to pembrolizumab in Sézary syndrome.

Authors:  Tianying Su; George E Duran; Alexa C Kwang; Nirasha Ramchurren; Steven P Fling; Youn H Kim; Michael S Khodadoust
Journal:  Oncoimmunology       Date:  2022-08-27       Impact factor: 7.723

6.  A novel risk score model based on fourteen chromatin regulators-based genes for predicting overall survival of patients with lower-grade gliomas.

Authors:  Yongfeng Zhang; Beibei Yu; Yunze Tian; Pengyu Ren; Boqiang Lyu; Longhui Fu; Huangtao Chen; Jianzhong Li; Shouping Gong
Journal:  Front Genet       Date:  2022-09-26       Impact factor: 4.772

Review 7.  Reprogramming T-Cell Metabolism for Better Anti-Tumor Immunity.

Authors:  Yu Ping; Chunyi Shen; Bo Huang; Yi Zhang
Journal:  Cells       Date:  2022-10-01       Impact factor: 7.666

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.